Skip to content

M
model-data-test
Commit 052263d5 authored by 桂秋月's avatar 桂秋月
Browse files
Options

添加真实uuid的判断

parent 3a89a0bc
Hide whitespace changes
Inline Side-by-side
Showing with 125662 additions and 47 deletions
.DS_Store 0 → 100644
View file @ 052263d5
File added
.idea/misc.xml
View file @ 052263d5
......@@ -3,21 +3,6 @@
<component name="JavaScriptSettings">
<option name="languageLevel" value="ES6" />
</component>
<component name="MavenImportPreferences">
<option name="generalSettings">
<MavenGeneralSettings>
<option name="localRepository" value="/usr/local/maven/loacalRepository" />
<option name="mavenHome" value="/usr/local/maven/apache-maven-3.5.2" />
<option name="userSettingsFile" value="/usr/local/maven/apache-maven-3.5.2/conf/settings.xml" />
</MavenGeneralSettings>
</option>
<option name="importingSettings">
<MavenImportingSettings>
<option name="generatedSourcesFolder" value="GENERATED_SOURCE_FOLDER" />
<option name="importAutomatically" value="true" />
</MavenImportingSettings>
</option>
</component>
<component name="ProjectInspectionProfilesVisibleTreeState">
<entry key="Project Default">
<profile-state>
......@@ -157,25 +142,7 @@
</profile-state>
</entry>
</component>
<component name="ProjectLevelVcsManager" settingsEditedManually="false">
<OptionsSetting value="true" id="Add" />
<OptionsSetting value="true" id="Remove" />
<OptionsSetting value="true" id="Checkout" />
<OptionsSetting value="true" id="Update" />
<OptionsSetting value="true" id="Status" />
<OptionsSetting value="true" id="Edit" />
<ConfirmationsSetting value="0" id="Add" />
<ConfirmationsSetting value="0" id="Remove" />
</component>
<component name="ProjectRootManager" version="2" languageLevel="JDK_1_6" default="false" assert-keyword="true" jdk-15="true" project-jdk-name="Python 3.6.10 (~/opt/anaconda3/envs/python36/bin/python3.6)" project-jdk-type="Python SDK" />
<component name="PyConsoleOptionsProvider">
<option name="myPythonConsoleState">
<console-settings sdk-home="$USER_HOME$/opt/anaconda3/envs/python36/bin/python3.6">
<option name="mySdkHome" value="$USER_HOME$/opt/anaconda3/envs/python36/bin/python3.6" />
<option name="myAddSourceRoots" value="true" />
</console-settings>
</option>
</component>
<component name="ProjectRootManager" version="2" languageLevel="JDK_1_6" project-jdk-name="Python 3.7" project-jdk-type="Python SDK" />
<component name="SvnConfiguration">
<configuration>$USER_HOME$/.subversion</configuration>
</component>
......
.idea/model-data-test.iml
View file @ 052263d5
......@@ -2,7 +2,9 @@
<module type="JAVA_MODULE" version="4">
<component name="NewModuleRootManager" inherit-compiler-output="true">
<exclude-output />
<content url="file://$MODULE_DIR$" />
<content url="file://$MODULE_DIR$">
<sourceFolder url="file://$MODULE_DIR$" isTestSource="false" />
</content>
<orderEntry type="inheritedJdk" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
......
.idea/workspace.xml 0 → 100755
View file @ 052263d5
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="AutoImportSettings">
<option name="autoReloadType" value="ALL" />
</component>
<component name="ChangeListManager">
<list default="true" id="65ec9bc1-9334-4fb0-a73d-621c8e760de6" name="Default Changelist" comment="">
<change beforePath="$PROJECT_DIR$/.idea/misc.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/misc.xml" afterDir="false" />
<change beforePath="$PROJECT_DIR$/.idea/model-data-test.iml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/model-data-test.iml" afterDir="false" />
<change beforePath="$PROJECT_DIR$/model_data_api/handler/Automatic_Handler.py" beforeDir="false" afterPath="$PROJECT_DIR$/model_data_api/handler/Automatic_Handler.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/model_data_api/handler/logic.py" beforeDir="false" afterPath="$PROJECT_DIR$/model_data_api/handler/logic.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/model_data_api/model/dataSetDetail_model.py" beforeDir="false" afterPath="$PROJECT_DIR$/model_data_api/model/dataSetDetail_model.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/model_data_api/model/featureData_model.py" beforeDir="false" afterPath="$PROJECT_DIR$/model_data_api/model/featureData_model.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/model_data_test/settings.py" beforeDir="false" afterPath="$PROJECT_DIR$/model_data_test/settings.py" afterDir="false" />
</list>
<option name="SHOW_DIALOG" value="false" />
<option name="HIGHLIGHT_CONFLICTS" value="true" />
<option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
<option name="LAST_RESOLUTION" value="IGNORE" />
</component>
<component name="Git.Settings">
<option name="RECENT_GIT_ROOT_PATH" value="$PROJECT_DIR$" />
</component>
<component name="JupyterTrust" id="ad4c8fd4-a4d0-4645-b595-4e06968dc07a" />
<component name="MavenImportPreferences">
<option name="generalSettings">
<MavenGeneralSettings>
<option name="localRepository" value="/usr/local/maven/loacalRepository" />
<option name="mavenHome" value="/usr/local/maven/apache-maven-3.5.2" />
<option name="userSettingsFile" value="/usr/local/maven/apache-maven-3.5.2/conf/settings.xml" />
</MavenGeneralSettings>
</option>
<option name="importingSettings">
<MavenImportingSettings>
<option name="generatedSourcesFolder" value="GENERATED_SOURCE_FOLDER" />
</MavenImportingSettings>
</option>
</component>
<component name="ProjectId" id="1re2OqHWm0oPmzaQtTT2J4s8MWf" />
<component name="ProjectViewState">
<option name="hideEmptyMiddlePackages" value="true" />
<option name="showLibraryContents" value="true" />
</component>
<component name="PropertiesComponent">
<property name="ASKED_ADD_EXTERNAL_FILES" value="true" />
<property name="RunOnceActivity.OpenProjectViewOnStart" value="true" />
<property name="RunOnceActivity.ShowReadmeOnStart" value="true" />
<property name="SHARE_PROJECT_CONFIGURATION_FILES" value="true" />
<property name="WebServerToolWindowFactoryState" value="false" />
<property name="aspect.path.notification.shown" value="true" />
<property name="last_opened_file_path" value="$PROJECT_DIR$" />
<property name="project.structure.last.edited" value="Modules" />
<property name="project.structure.proportion" value="0.15" />
<property name="project.structure.side.proportion" value="0.2" />
<property name="settings.editor.selected.configurable" value="preferences.lookFeel" />
</component>
<component name="PyConsoleOptionsProvider">
<option name="myPythonConsoleState">
<console-settings sdk-home="$USER_HOME$/opt/anaconda3/envs/python36/bin/python3.6">
<option name="mySdkHome" value="$USER_HOME$/opt/anaconda3/envs/python36/bin/python3.6" />
</console-settings>
</option>
</component>
<component name="RunManager">
<configuration name="startup" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
<module name="model-data-test" />
<option name="INTERPRETER_OPTIONS" value="" />
<option name="PARENT_ENVS" value="true" />
<envs>
<env name="PYTHONUNBUFFERED" value="1" />
</envs>
<option name="SDK_HOME" value="/usr/local/bin/python3.7" />
<option name="WORKING_DIRECTORY" value="$PROJECT_DIR$" />
<option name="IS_MODULE_SDK" value="false" />
<option name="ADD_CONTENT_ROOTS" value="true" />
<option name="ADD_SOURCE_ROOTS" value="true" />
<EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
<option name="SCRIPT_NAME" value="$PROJECT_DIR$/startup.py" />
<option name="PARAMETERS" value="" />
<option name="SHOW_COMMAND_LINE" value="false" />
<option name="EMULATE_TERMINAL" value="false" />
<option name="MODULE_MODE" value="false" />
<option name="REDIRECT_INPUT" value="false" />
<option name="INPUT_FILE" value="" />
<method v="2" />
</configuration>
<recent_temporary>
<list>
<item itemvalue="Python.startup" />
</list>
</recent_temporary>
</component>
<component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
<component name="SvnConfiguration">
<configuration>$USER_HOME$/.subversion</configuration>
</component>
<component name="TaskManager">
<task active="true" id="Default" summary="Default task">
<changelist id="65ec9bc1-9334-4fb0-a73d-621c8e760de6" name="Default Changelist" comment="" />
<created>1619322205478</created>
<option name="number" value="Default" />
<option name="presentableId" value="Default" />
<updated>1619322205478</updated>
<workItem from="1619322207223" duration="12323000" />
<workItem from="1619419245278" duration="2335000" />
<workItem from="1619490114301" duration="1847000" />
<workItem from="1620440234843" duration="1666000" />
<workItem from="1621232492042" duration="2693000" />
<workItem from="1621246463980" duration="265000" />
<workItem from="1621392800825" duration="231000" />
<workItem from="1626956770039" duration="546000" />
</task>
<servers />
</component>
<component name="TypeScriptGeneratedFilesManager">
<option name="version" value="1" />
</component>
<component name="UnknownFeatures">
<option featureType="com.intellij.fileTypeFactory" implementationName="*.log" />
</component>
<component name="Vcs.Log.Tabs.Properties">
<option name="TAB_STATES">
<map>
<entry key="MAIN">
<value>
<State />
</value>
</entry>
</map>
</option>
</component>
<component name="XDebuggerManager">
<breakpoint-manager>
<breakpoints>
<line-breakpoint enabled="true" suspend="THREAD" type="python-line">
<url>file://$PROJECT_DIR$/model_data_api/handler/Automatic_Handler.py</url>
<line>75</line>
<option name="timeStamp" value="4" />
</line-breakpoint>
<line-breakpoint enabled="true" suspend="THREAD" type="python-line">
<url>file://$PROJECT_DIR$/model_data_api/handler/Automatic_Handler.py</url>
<line>30</line>
<option name="timeStamp" value="9" />
</line-breakpoint>
<line-breakpoint enabled="true" suspend="THREAD" type="python-line">
<url>file://$PROJECT_DIR$/model_data_api/handler/logic.py</url>
<line>96</line>
<option name="timeStamp" value="12" />
</line-breakpoint>
<line-breakpoint enabled="true" suspend="THREAD" type="python-line">
<url>file://$PROJECT_DIR$/model_data_api/handler/logic.py</url>
<line>132</line>
<option name="timeStamp" value="13" />
</line-breakpoint>
</breakpoints>
</breakpoint-manager>
</component>
<component name="XSLT-Support.FileAssociations.UIState">
<expand />
<select />
</component>
</project>
\ No newline at end of file
Pipfile 0 → 100755
View file @ 052263d5
[[source]]
url = "https://mirrors.aliyun.com/pypi/simple/"
verify_ssl = true
name = "pypi"
[packages]
celery = "*"
tasks = "*"
tornado = "*"
tornado-sqlalchemy = "*"
sqlalchemy = "*"
pymysql = "*"
pandas = "*"
requests = "*"
tqdm = "*"
[dev-packages]
[requires]
python_version = "3.7"
Pipfile.lock 0 → 100644
View file @ 052263d5
{
"_meta": {
"hash": {
"sha256": "65bd3bd737526ff2419b6c3d0d79d8525eeac5a052f1830597d8019996f18938"
},
"pipfile-spec": 6,
"requires": {
"python_version": "3.7"
},
"sources": [
{
"name": "pypi",
"url": "https://mirrors.aliyun.com/pypi/simple/",
"verify_ssl": true
}
]
},
"default": {
"amqp": {
"hashes": [
"sha256:03e16e94f2b34c31f8bf1206d8ddd3ccaa4c315f7f6a1879b7b1210d229568c2",
"sha256:493a2ac6788ce270a2f6a765b017299f60c1998f5a8617908ee9be082f7300fb"
],
"markers": "python_version >= '3.6'",
"version": "==5.0.6"
},
"billiard": {
"hashes": [
"sha256:299de5a8da28a783d51b197d496bef4f1595dd023a93a4f59dde1886ae905547",
"sha256:87103ea78fa6ab4d5c751c4909bcff74617d985de7fa8b672cf8618afd5a875b"
],
"version": "==3.6.4.0"
},
"celery": {
"hashes": [
"sha256:5e8d364e058554e83bbb116e8377d90c79be254785f357cb2cec026e79febe13",
"sha256:f4efebe6f8629b0da2b8e529424de376494f5b7a743c321c8a2ddc2b1414921c"
],
"index": "pypi",
"version": "==5.0.5"
},
"certifi": {
"hashes": [
"sha256:1a4995114262bffbc2413b159f2a1a480c969de6e6eb13ee966d470af86af59c",
"sha256:719a74fb9e33b9bd44cc7f3a8d94bc35e4049deebe19ba7d8e108280cfd59830"
],
"version": "==2020.12.5"
},
"chardet": {
"hashes": [
"sha256:0d6f53a15db4120f2b08c94f11e7d93d2c911ee118b6b30a04ec3ee8310179fa",
"sha256:f864054d66fd9118f2e67044ac8981a54775ec5b67aed0441892edb553d21da5"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
"version": "==4.0.0"
},
"click": {
"hashes": [
"sha256:d2b5255c7c6349bc1bd1e59e08cd12acbbd63ce649f2588755783aa94dfb6b1a",
"sha256:dacca89f4bfadd5de3d7489b7c8a566eee0d3676333fbb50030263894c38c0dc"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
"version": "==7.1.2"
},
"click-didyoumean": {
"hashes": [
"sha256:112229485c9704ff51362fe34b2d4f0b12fc71cc20f6d2b3afabed4b8bfa6aeb"
],
"version": "==0.0.3"
},
"click-plugins": {
"hashes": [
"sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b",
"sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"
],
"version": "==1.1.1"
},
"click-repl": {
"hashes": [
"sha256:9c4c3d022789cae912aad8a3f5e1d7c2cdd016ee1225b5212ad3e8691563cda5",
"sha256:b9f29d52abc4d6059f8e276132a111ab8d94980afe6a5432b9d996544afa95d5"
],
"version": "==0.1.6"
},
"datadispatch": {
"hashes": [
"sha256:3c0456934e99f21137332deebbda05713dc07fcb142dfc01ef83d6b17aeaf08e",
"sha256:527ad534881d7f6144a8ff643c260a3d2ae0d50e8ee24ec4b0fdae72d6c7beab"
],
"version": "==1.0.0"
},
"greenlet": {
"hashes": [
"sha256:0a77691f0080c9da8dfc81e23f4e3cffa5accf0f5b56478951016d7cfead9196",
"sha256:0ddd77586553e3daf439aa88b6642c5f252f7ef79a39271c25b1d4bf1b7cbb85",
"sha256:111cfd92d78f2af0bc7317452bd93a477128af6327332ebf3c2be7df99566683",
"sha256:122c63ba795fdba4fc19c744df6277d9cfd913ed53d1a286f12189a0265316dd",
"sha256:181300f826625b7fd1182205b830642926f52bd8cdb08b34574c9d5b2b1813f7",
"sha256:1a1ada42a1fd2607d232ae11a7b3195735edaa49ea787a6d9e6a53afaf6f3476",
"sha256:1bb80c71de788b36cefb0c3bb6bfab306ba75073dbde2829c858dc3ad70f867c",
"sha256:1d1d4473ecb1c1d31ce8fd8d91e4da1b1f64d425c1dc965edc4ed2a63cfa67b2",
"sha256:292e801fcb3a0b3a12d8c603c7cf340659ea27fd73c98683e75800d9fd8f704c",
"sha256:2c65320774a8cd5fdb6e117c13afa91c4707548282464a18cf80243cf976b3e6",
"sha256:4365eccd68e72564c776418c53ce3c5af402bc526fe0653722bc89efd85bf12d",
"sha256:5352c15c1d91d22902582e891f27728d8dac3bd5e0ee565b6a9f575355e6d92f",
"sha256:58ca0f078d1c135ecf1879d50711f925ee238fe773dfe44e206d7d126f5bc664",
"sha256:5d4030b04061fdf4cbc446008e238e44936d77a04b2b32f804688ad64197953c",
"sha256:5d69bbd9547d3bc49f8a545db7a0bd69f407badd2ff0f6e1a163680b5841d2b0",
"sha256:5f297cb343114b33a13755032ecf7109b07b9a0020e841d1c3cedff6602cc139",
"sha256:62afad6e5fd70f34d773ffcbb7c22657e1d46d7fd7c95a43361de979f0a45aef",
"sha256:647ba1df86d025f5a34043451d7c4a9f05f240bee06277a524daad11f997d1e7",
"sha256:719e169c79255816cdcf6dccd9ed2d089a72a9f6c42273aae12d55e8d35bdcf8",
"sha256:7cd5a237f241f2764324396e06298b5dee0df580cf06ef4ada0ff9bff851286c",
"sha256:875d4c60a6299f55df1c3bb870ebe6dcb7db28c165ab9ea6cdc5d5af36bb33ce",
"sha256:90b6a25841488cf2cb1c8623a53e6879573010a669455046df5f029d93db51b7",
"sha256:94620ed996a7632723a424bccb84b07e7b861ab7bb06a5aeb041c111dd723d36",
"sha256:b5f1b333015d53d4b381745f5de842f19fe59728b65f0fbb662dafbe2018c3a5",
"sha256:c5b22b31c947ad8b6964d4ed66776bcae986f73669ba50620162ba7c832a6b6a",
"sha256:c93d1a71c3fe222308939b2e516c07f35a849c5047f0197442a4d6fbcb4128ee",
"sha256:cdb90267650c1edb54459cdb51dab865f6c6594c3a47ebd441bc493360c7af70",
"sha256:cfd06e0f0cc8db2a854137bd79154b61ecd940dce96fad0cba23fe31de0b793c",
"sha256:d3789c1c394944084b5e57c192889985a9f23bd985f6d15728c745d380318128",
"sha256:da7d09ad0f24270b20f77d56934e196e982af0d0a2446120cb772be4e060e1a2",
"sha256:df3e83323268594fa9755480a442cabfe8d82b21aba815a71acf1bb6c1776218",
"sha256:df8053867c831b2643b2c489fe1d62049a98566b1646b194cc815f13e27b90df",
"sha256:e1128e022d8dce375362e063754e129750323b67454cac5600008aad9f54139e",
"sha256:e6e9fdaf6c90d02b95e6b0709aeb1aba5affbbb9ccaea5502f8638e4323206be",
"sha256:eac8803c9ad1817ce3d8d15d1bb82c2da3feda6bee1153eec5c58fa6e5d3f770",
"sha256:eb333b90036358a0e2c57373f72e7648d7207b76ef0bd00a4f7daad1f79f5203",
"sha256:ed1d1351f05e795a527abc04a0d82e9aecd3bdf9f46662c36ff47b0b00ecaf06",
"sha256:f3dc68272990849132d6698f7dc6df2ab62a88b0d36e54702a8fd16c0490e44f",
"sha256:f59eded163d9752fd49978e0bab7a1ff21b1b8d25c05f0995d140cc08ac83379",
"sha256:f5e2d36c86c7b03c94b8459c3bd2c9fe2c7dab4b258b8885617d44a22e453fb7",
"sha256:f6f65bf54215e4ebf6b01e4bb94c49180a589573df643735107056f7a910275b",
"sha256:f8450d5ef759dbe59f84f2c9f77491bb3d3c44bc1a573746daf086e70b14c243",
"sha256:f97d83049715fd9dec7911860ecf0e17b48d8725de01e45de07d8ac0bd5bc378"
],
"markers": "python_version >= '3'",
"version": "==1.0.0"
},
"idna": {
"hashes": [
"sha256:b307872f855b18632ce0c21c5e45be78c0ea7ae4c15c828c20788b26921eb3f6",
"sha256:b97d804b1e9b523befed77c48dacec60e6dcb0b5391d57af6a65a312a90648c0"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
"version": "==2.10"
},
"importlib-metadata": {
"hashes": [
"sha256:8c501196e49fb9df5df43833bdb1e4328f64847763ec8a50703148b73784d581",
"sha256:d7eb1dea6d6a6086f8be21784cc9e3bcfa55872b52309bc5fad53a8ea444465d"
],
"markers": "python_version < '3.8'",
"version": "==4.0.1"
},
"kombu": {
"hashes": [
"sha256:6dc509178ac4269b0e66ab4881f70a2035c33d3a622e20585f965986a5182006",
"sha256:f4965fba0a4718d47d470beeb5d6446e3357a62402b16c510b6a2f251e05ac3c"
],
"markers": "python_version >= '3.6'",
"version": "==5.0.2"
},
"numpy": {
"hashes": [
"sha256:2428b109306075d89d21135bdd6b785f132a1f5a3260c371cee1fae427e12727",
"sha256:377751954da04d4a6950191b20539066b4e19e3b559d4695399c5e8e3e683bf6",
"sha256:4703b9e937df83f5b6b7447ca5912b5f5f297aba45f91dbbbc63ff9278c7aa98",
"sha256:471c0571d0895c68da309dacee4e95a0811d0a9f9f532a48dc1bea5f3b7ad2b7",
"sha256:61d5b4cf73622e4d0c6b83408a16631b670fc045afd6540679aa35591a17fe6d",
"sha256:6c915ee7dba1071554e70a3664a839fbc033e1d6528199d4621eeaaa5487ccd2",
"sha256:6e51e417d9ae2e7848314994e6fc3832c9d426abce9328cf7571eefceb43e6c9",
"sha256:719656636c48be22c23641859ff2419b27b6bdf844b36a2447cb39caceb00935",
"sha256:780ae5284cb770ade51d4b4a7dce4faa554eb1d88a56d0e8b9f35fca9b0270ff",
"sha256:878922bf5ad7550aa044aa9301d417e2d3ae50f0f577de92051d739ac6096cee",
"sha256:924dc3f83de20437de95a73516f36e09918e9c9c18d5eac520062c49191025fb",
"sha256:97ce8b8ace7d3b9288d88177e66ee75480fb79b9cf745e91ecfe65d91a856042",
"sha256:9c0fab855ae790ca74b27e55240fe4f2a36a364a3f1ebcfd1fb5ac4088f1cec3",
"sha256:9cab23439eb1ebfed1aaec9cd42b7dc50fc96d5cd3147da348d9161f0501ada5",
"sha256:a8e6859913ec8eeef3dbe9aed3bf475347642d1cdd6217c30f28dee8903528e6",
"sha256:aa046527c04688af680217fffac61eec2350ef3f3d7320c07fd33f5c6e7b4d5f",
"sha256:abc81829c4039e7e4c30f7897938fa5d4916a09c2c7eb9b244b7a35ddc9656f4",
"sha256:bad70051de2c50b1a6259a6df1daaafe8c480ca98132da98976d8591c412e737",
"sha256:c73a7975d77f15f7f68dacfb2bca3d3f479f158313642e8ea9058eea06637931",
"sha256:d15007f857d6995db15195217afdbddfcd203dfaa0ba6878a2f580eaf810ecd6",
"sha256:d76061ae5cab49b83a8cf3feacefc2053fac672728802ac137dd8c4123397677",
"sha256:e8e4fbbb7e7634f263c5b0150a629342cc19b47c5eba8d1cd4363ab3455ab576",
"sha256:e9459f40244bb02b2f14f6af0cd0732791d72232bbb0dc4bab57ef88e75f6935",
"sha256:edb1f041a9146dcf02cd7df7187db46ab524b9af2515f392f337c7cbbf5b52cd"
],
"markers": "python_version >= '3.7'",
"version": "==1.20.2"
},
"pandas": {
"hashes": [
"sha256:167693a80abc8eb28051fbd184c1b7afd13ce2c727a5af47b048f1ea3afefff4",
"sha256:2111c25e69fa9365ba80bbf4f959400054b2771ac5d041ed19415a8b488dc70a",
"sha256:298f0553fd3ba8e002c4070a723a59cdb28eda579f3e243bc2ee397773f5398b",
"sha256:2b063d41803b6a19703b845609c0b700913593de067b552a8b24dd8eeb8c9895",
"sha256:2cb7e8f4f152f27dc93f30b5c7a98f6c748601ea65da359af734dd0cf3fa733f",
"sha256:52d2472acbb8a56819a87aafdb8b5b6d2b3386e15c95bde56b281882529a7ded",
"sha256:612add929bf3ba9d27b436cc8853f5acc337242d6b584203f207e364bb46cb12",
"sha256:649ecab692fade3cbfcf967ff936496b0cfba0af00a55dfaacd82bdda5cb2279",
"sha256:68d7baa80c74aaacbed597265ca2308f017859123231542ff8a5266d489e1858",
"sha256:8d4c74177c26aadcfb4fd1de6c1c43c2bf822b3e0fc7a9b409eeaf84b3e92aaa",
"sha256:971e2a414fce20cc5331fe791153513d076814d30a60cd7348466943e6e909e4",
"sha256:9db70ffa8b280bb4de83f9739d514cd0735825e79eef3a61d312420b9f16b758",
"sha256:b730add5267f873b3383c18cac4df2527ac4f0f0eed1c6cf37fcb437e25cf558",
"sha256:bd659c11a4578af740782288cac141a322057a2e36920016e0fc7b25c5a4b686",
"sha256:c601c6fdebc729df4438ec1f62275d6136a0dd14d332fc0e8ce3f7d2aadb4dd6",
"sha256:d0877407359811f7b853b548a614aacd7dea83b0c0c84620a9a643f180060950"
],
"index": "pypi",
"version": "==1.2.4"
},
"prompt-toolkit": {
"hashes": [
"sha256:bf00f22079f5fadc949f42ae8ff7f05702826a97059ffcc6281036ad40ac6f04",
"sha256:e1b4f11b9336a28fa11810bc623c357420f69dfdb6d2dac41ca2c21a55c033bc"
],
"markers": "python_full_version >= '3.6.1'",
"version": "==3.0.18"
},
"pymysql": {
"hashes": [
"sha256:41fc3a0c5013d5f039639442321185532e3e2c8924687abe6537de157d403641",
"sha256:816927a350f38d56072aeca5dfb10221fe1dc653745853d30a216637f5d7ad36"
],
"index": "pypi",
"version": "==1.0.2"
},
"python-dateutil": {
"hashes": [
"sha256:73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c",
"sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
"version": "==2.8.1"
},
"pytz": {
"hashes": [
"sha256:83a4a90894bf38e243cf052c8b58f381bfe9a7a483f6a9cab140bc7f702ac4da",
"sha256:eb10ce3e7736052ed3623d49975ce333bcd712c7bb19a58b9e2089d4057d0798"
],
"version": "==2021.1"
},
"requests": {
"hashes": [
"sha256:27973dd4a904a4f13b263a19c866c13b92a39ed1c964655f025f3f8d3d75b804",
"sha256:c210084e36a42ae6b9219e00e48287def368a26d03a048ddad7bfee44f75871e"
],
"index": "pypi",
"version": "==2.25.1"
},
"six": {
"hashes": [
"sha256:30639c035cdb23534cd4aa2dd52c3bf48f06e5f4a941509c8bafd8ce11080259",
"sha256:8b74bedcbbbaca38ff6d7491d76f2b06b3592611af620f8426e82dddb04a5ced"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
"version": "==1.15.0"
},
"sqlalchemy": {
"hashes": [
"sha256:0140f6dac2659fa6783e7029085ab0447d8eb23cf4d831fb907588d27ba158f7",
"sha256:034b42a6a59bf4ddc57e5a38a9dbac83ccd94c0b565ba91dba4ff58149706028",
"sha256:03a503ecff0cc2be3ad4dafd220eaff13721edb11c191670b7662932fb0a5c3a",
"sha256:069de3a701d33709236efe0d06f38846b738b19c63d45cc47f54590982ba7802",
"sha256:1735e06a3d5b0793d5ee2d952df8a5c63edaff6383c2210c9b5c93dc2ea4c315",
"sha256:19633df6be629200ff3c026f2837e1dd17908fb1bcea860290a5a45e6fa5148e",
"sha256:1e14fa32969badef9c309f55352e5c46f321bd29f7c600556caacdaa3eddfcf6",
"sha256:31e941d6db8b026bc63e46ef71e877913f128bd44260b90c645432626b7f9a47",
"sha256:452c4e002be727cb6f929dbd32bbc666a0921b86555b8af09709060ed3954bd3",
"sha256:45a720029756800628359192630fffdc9660ab6f27f0409bd24d9e09d75d6c18",
"sha256:4a2e7f037d3ca818d6d0490e3323fd451545f580df30d62b698da2f247015a34",
"sha256:4a7d4da2acf6d5d068fb41c48950827c49c3c68bfb46a1da45ea8fbf7ed4b471",
"sha256:4ad4044eb86fbcbdff2106e44f479fbdac703d77860b3e19988c8a8786e73061",
"sha256:4f631edf45a943738fa77612e85fc5c5d3fb637c4f5a530f7eedd1a7cd7a70a7",
"sha256:6389b10e23329dc8b5600c1a84e3da2628d0f437d8a5cd05aefd1470ec571dd1",
"sha256:6ebd58e73b7bd902688c0bb8dbabb0c36b756f02cc7b27ad5efa2f380c611f95",
"sha256:7180830ea1082b96b94884bc352b274e29b45151b6ee911bf1fd79cba2de659b",
"sha256:789be639501445d85fd4ca41d04f0f5c6cbb6deb0c6826aaa6f22774fe84ef94",
"sha256:7d89add44938ea4f52c7641d5805c9e154fed4381e874ef3221483eeb191a96d",
"sha256:842b0d4698381aac047f8ae57409c90b7e63ebabf5bc02814ddc8eaefd13499e",
"sha256:8f96d4b6a49d3f0f109365bb6303ae5d266d3f90280ca68cf8b2c46032491038",
"sha256:961b089e64c2ad29ad367487dd3ba1aa3eeba56bc82037ce91732baaa0f6ca90",
"sha256:96de1d4a2e05d4a017087cb29cd6a8ebfeecfd0e9f872880b1a589f011c1c02e",
"sha256:98214f04802a3fc740038744d8981a8f2fdca710f791ca125fc4792737d9f3a7",
"sha256:9cf94161cb55507cee147bf8abcfd3c076b353ad18743296764dd81108ea74f8",
"sha256:9fdf0713166f33e5e6ea98cf59deb305cb323131277f6880de6c509f468076f8",
"sha256:a41ab83ecfadf38a47bdfaf4e488f71579df47a711e1ab1dce30d34c7c25bd00",
"sha256:ac14fee167653ec6dee32d6aa4d501d90ae1bfbbc3eb5816940bccf227f0d617",
"sha256:b8b7d66ee8b8ac272adce0af1342a60854f0d89686e6d3318127a6a82a2f765c",
"sha256:bb1072fdf48ba870c0fe81bee8babe4ba2f096fb56bb4f3e0c2386a7626e405c",
"sha256:cd823071b97c1a6ac3af9e43b5d861126a1304033dcd18dfe354a02ec45642fe",
"sha256:d08173144aebdf30c21a331b532db16535cfa83deed12e8703fa6c67c0894ffc",
"sha256:e7d76312e904aa4ea221a92c0bc2e299ad46e4580e2d72ca1f7e6d31dce5bfab",
"sha256:f772e4428d413c0affe2a34836278fbe9df9a9c0940705860c2d3a4b50af1a66"
],
"index": "pypi",
"version": "==1.4.11"
},
"tasks": {
"hashes": [
"sha256:94719dccc369129c4e626486cc0e681ae3d3b4d631d9a60cb66c7fd7f351e711",
"sha256:f5a387c728dbee5017b35802754598fc872a5b0f2bf01422dce216182ad73d4f"
],
"index": "pypi",
"version": "==2.7.0"
},
"tornado": {
"hashes": [
"sha256:0a00ff4561e2929a2c37ce706cb8233b7907e0cdc22eab98888aca5dd3775feb",
"sha256:0d321a39c36e5f2c4ff12b4ed58d41390460f798422c4504e09eb5678e09998c",
"sha256:1e8225a1070cd8eec59a996c43229fe8f95689cb16e552d130b9793cb570a288",
"sha256:20241b3cb4f425e971cb0a8e4ffc9b0a861530ae3c52f2b0434e6c1b57e9fd95",
"sha256:25ad220258349a12ae87ede08a7b04aca51237721f63b1808d39bdb4b2164558",
"sha256:33892118b165401f291070100d6d09359ca74addda679b60390b09f8ef325ffe",
"sha256:33c6e81d7bd55b468d2e793517c909b139960b6c790a60b7991b9b6b76fb9791",
"sha256:3447475585bae2e77ecb832fc0300c3695516a47d46cefa0528181a34c5b9d3d",
"sha256:34ca2dac9e4d7afb0bed4677512e36a52f09caa6fded70b4e3e1c89dbd92c326",
"sha256:3e63498f680547ed24d2c71e6497f24bca791aca2fe116dbc2bd0ac7f191691b",
"sha256:548430be2740e327b3fe0201abe471f314741efcb0067ec4f2d7dcfb4825f3e4",
"sha256:6196a5c39286cc37c024cd78834fb9345e464525d8991c21e908cc046d1cc02c",
"sha256:61b32d06ae8a036a6607805e6720ef00a3c98207038444ba7fd3d169cd998910",
"sha256:6286efab1ed6e74b7028327365cf7346b1d777d63ab30e21a0f4d5b275fc17d5",
"sha256:65d98939f1a2e74b58839f8c4dab3b6b3c1ce84972ae712be02845e65391ac7c",
"sha256:66324e4e1beede9ac79e60f88de548da58b1f8ab4b2f1354d8375774f997e6c0",
"sha256:6c77c9937962577a6a76917845d06af6ab9197702a42e1346d8ae2e76b5e3675",
"sha256:70dec29e8ac485dbf57481baee40781c63e381bebea080991893cd297742b8fd",
"sha256:7250a3fa399f08ec9cb3f7b1b987955d17e044f1ade821b32e5f435130250d7f",
"sha256:748290bf9112b581c525e6e6d3820621ff020ed95af6f17fedef416b27ed564c",
"sha256:7da13da6f985aab7f6f28debab00c67ff9cbacd588e8477034c0652ac141feea",
"sha256:8f959b26f2634a091bb42241c3ed8d3cedb506e7c27b8dd5c7b9f745318ddbb6",
"sha256:9de9e5188a782be6b1ce866e8a51bc76a0fbaa0e16613823fc38e4fc2556ad05",
"sha256:a48900ecea1cbb71b8c71c620dee15b62f85f7c14189bdeee54966fbd9a0c5bd",
"sha256:b87936fd2c317b6ee08a5741ea06b9d11a6074ef4cc42e031bc6403f82a32575",
"sha256:c77da1263aa361938476f04c4b6c8916001b90b2c2fdd92d8d535e1af48fba5a",
"sha256:cb5ec8eead331e3bb4ce8066cf06d2dfef1bfb1b2a73082dfe8a161301b76e37",
"sha256:cc0ee35043162abbf717b7df924597ade8e5395e7b66d18270116f8745ceb795",
"sha256:d14d30e7f46a0476efb0deb5b61343b1526f73ebb5ed84f23dc794bdb88f9d9f",
"sha256:d371e811d6b156d82aa5f9a4e08b58debf97c302a35714f6f45e35139c332e32",
"sha256:d3d20ea5782ba63ed13bc2b8c291a053c8d807a8fa927d941bd718468f7b950c",
"sha256:d3f7594930c423fd9f5d1a76bee85a2c36fd8b4b16921cae7e965f22575e9c01",
"sha256:dcef026f608f678c118779cd6591c8af6e9b4155c44e0d1bc0c87c036fb8c8c4",
"sha256:e0791ac58d91ac58f694d8d2957884df8e4e2f6687cdf367ef7eb7497f79eaa2",
"sha256:e385b637ac3acaae8022e7e47dfa7b83d3620e432e3ecb9a3f7f58f150e50921",
"sha256:e519d64089b0876c7b467274468709dadf11e41d65f63bba207e04217f47c085",
"sha256:e7229e60ac41a1202444497ddde70a48d33909e484f96eb0da9baf8dc68541df",
"sha256:ed3ad863b1b40cd1d4bd21e7498329ccaece75db5a5bf58cd3c9f130843e7102",
"sha256:f0ba29bafd8e7e22920567ce0d232c26d4d47c8b5cf4ed7b562b5db39fa199c5",
"sha256:fa2ba70284fa42c2a5ecb35e322e68823288a4251f9ba9cc77be04ae15eada68",
"sha256:fba85b6cd9c39be262fcd23865652920832b61583de2a2ca907dbd8e8a8c81e5"
],
"index": "pypi",
"version": "==6.1"
},
"tornado-sqlalchemy": {
"hashes": [
"sha256:d21527a06821c0d9b06cf5e87f3ca2fb6a665db2787b7b6576d225a01633cab9",
"sha256:f37e59c376aa7661beb96992977c64e6b0baf5cbe74c41ccc0bf3b25dee0e637"
],
"index": "pypi",
"version": "==0.7.0"
},
"tqdm": {
"hashes": [
"sha256:daec693491c52e9498632dfbe9ccfc4882a557f5fa08982db1b4d3adbe0887c3",
"sha256:ebdebdb95e3477ceea267decfc0784859aa3df3e27e22d23b83e9b272bf157ae"
],
"index": "pypi",
"version": "==4.60.0"
},
"typing-extensions": {
"hashes": [
"sha256:7cb407020f00f7bfc3cb3e7881628838e69d8f3fcab2f64742a5e76b2f841918",
"sha256:99d4073b617d30288f569d3f13d2bd7548c3a7e4c8de87db09a9d29bb3a4a60c",
"sha256:dafc7639cde7f1b6e1acc0f457842a83e722ccca8eef5270af2d74792619a89f"
],
"markers": "python_version < '3.8'",
"version": "==3.7.4.3"
},
"urllib3": {
"hashes": [
"sha256:2f4da4594db7e1e110a944bb1b551fdf4e6c136ad42e4234131391e21eb5b0df",
"sha256:e7b021f7241115872f92f43c6508082facffbd1c048e3c6e2bb9c2a157e28937"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4' and python_version < '4.0'",
"version": "==1.26.4"
},
"vine": {
"hashes": [
"sha256:4c9dceab6f76ed92105027c49c823800dd33cacce13bdedc5b914e3514b7fb30",
"sha256:7d3b1624a953da82ef63462013bbd271d3eb75751489f9807598e8f340bd637e"
],
"markers": "python_version >= '3.6'",
"version": "==5.0.0"
},
"wcwidth": {
"hashes": [
"sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784",
"sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"
],
"version": "==0.2.5"
},
"zipp": {
"hashes": [
"sha256:3607921face881ba3e026887d8150cca609d517579abe052ac81fc5aeffdbd76",
"sha256:51cb66cc54621609dd593d1787f286ee42a5c0adbb4b29abea5a63edc3e03098"
],
"markers": "python_version >= '3.6'",
"version": "==3.4.1"
}
},
"develop": {}
}
data/uuid.csv 0 → 100644
View file @ 052263d5
This source diff could not be displayed because it is too large. You can view the blob instead.
logs/2021-04-25.log 0 → 100755
View file @ 052263d5
This source diff could not be displayed because it is too large. You can view the blob instead.
logs/2021-04-26.log 0 → 100644
View file @ 052263d5
[2021-04-26 14:46:51 web.py:log_request:2243 WARNING] 405 GET /api/model/exec (192.168.29.38) 49.35ms
[2021-04-26 14:46:56 web.py:log_request:2243 INFO] 200 POST /api/model/exec (192.168.29.38) 7.01ms
[2021-04-26 14:50:24 web.py:log_request:2243 INFO] 200 POST /api/model/exec (192.168.29.38) 9.25ms
[2021-04-26 15:43:17 web.py:log_request:2243 WARNING] 405 GET /api/automatic (::1) 30.24ms
[2021-04-26 15:43:22 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-26 15:43:22 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:22 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-26 15:43:22 log.py:info:117 INFO] [generated in 0.00050s] {}
[2021-04-26 15:43:22 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-26 15:43:22 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:22 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:22 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-26 15:43:22 log.py:info:117 INFO] [generated in 0.00044s] {'name_1': 'fst_assemble_flx_v8_score'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-26 15:43:23 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:23 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-26 15:43:23 log.py:info:117 INFO] [generated in 0.00044s] {}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-26 15:43:23 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:23 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT assert_datail.assert_name AS assert_datail_assert_name, assert_datail.assert_content AS assert_datail_assert_content, assert_datail.assert_type AS assert_datail_assert_type, assert_datail.assert_value AS assert_datail_assert_value, assert_datail.assert_gdp AS assert_datail_assert_gdp, assert_datail.data_type AS assert_datail_data_type, assert_datail.data_round AS assert_datail_data_round
FROM assert_datail
WHERE assert_datail.assert_name = %(assert_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [generated in 0.00049s] {'assert_name_1': '模型测试'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT assert_datail.assert_name AS assert_datail_assert_name, assert_datail.assert_content AS assert_datail_assert_content, assert_datail.assert_type AS assert_datail_assert_type, assert_datail.assert_value AS assert_datail_assert_value, assert_datail.assert_gdp AS assert_datail_assert_gdp, assert_datail.data_type AS assert_datail_data_type, assert_datail.data_round AS assert_datail_data_round
FROM assert_datail
WHERE assert_datail.assert_name = %(assert_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [cached since 0.01349s ago] {'assert_name_1': '模型测试'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT assert_datail.assert_name AS assert_datail_assert_name, assert_datail.assert_content AS assert_datail_assert_content, assert_datail.assert_type AS assert_datail_assert_type, assert_datail.assert_value AS assert_datail_assert_value, assert_datail.assert_gdp AS assert_datail_assert_gdp, assert_datail.data_type AS assert_datail_data_type, assert_datail.data_round AS assert_datail_data_round
FROM assert_datail
WHERE assert_datail.assert_name = %(assert_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [cached since 0.02663s ago] {'assert_name_1': '模型测试'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT assert_datail.assert_name AS assert_datail_assert_name, assert_datail.assert_content AS assert_datail_assert_content, assert_datail.assert_type AS assert_datail_assert_type, assert_datail.assert_value AS assert_datail_assert_value, assert_datail.assert_gdp AS assert_datail_assert_gdp, assert_datail.data_type AS assert_datail_data_type, assert_datail.data_round AS assert_datail_data_round
FROM assert_datail
WHERE assert_datail.assert_name = %(assert_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [cached since 0.05768s ago] {'assert_name_1': '模型测试'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT assert_datail.assert_name AS assert_datail_assert_name, assert_datail.assert_content AS assert_datail_assert_content, assert_datail.assert_type AS assert_datail_assert_type, assert_datail.assert_value AS assert_datail_assert_value, assert_datail.assert_gdp AS assert_datail_assert_gdp, assert_datail.data_type AS assert_datail_data_type, assert_datail.data_round AS assert_datail_data_round
FROM assert_datail
WHERE assert_datail.assert_name = %(assert_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [cached since 0.06918s ago] {'assert_name_1': '模型测试'}
[2021-04-26 15:43:23 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [generated in 0.00036s] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:23 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:23 log.py:info:117 INFO] [generated in 0.00033s] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 23, 727561), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:23 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.385s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.3777s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 105923), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.4587s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.4512s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 179467), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.5253s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.5184s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 246670), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.8848s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.8751s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 603257), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.9766s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 0.9675s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 695586), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 1.059s ago] {'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:24 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 1.052s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 24, 779798), 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'is_active_1': 1}
[2021-04-26 15:43:24 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:24 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:24 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:24 log.py:info:117 INFO] [cached since 1.12s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.33s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 58558), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.409s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.399s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 127108), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.466s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.484s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 212305), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.553s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.545s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 273010), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.613s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.601s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 329437), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.889s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.877s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 605364), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.965s ago] {'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 1.954s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 682567), 'feature_name_1': 'third_data_source#tc_universal_model_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.021s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.012s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 739884), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.089s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.079s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 807659), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:25 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:25 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:25 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.149s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:25 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:25 log.py:info:117 INFO] [cached since 2.139s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 25, 867436), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.634s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.622s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 349804), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.694s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.906s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 634577), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.974s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 2.964s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 692270), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.032s ago] {'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.023s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 751531), 'feature_name_1': 'third_data_source#xy_model3_score', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.113s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.102s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 830633), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:26 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:26 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.176s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:26 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:26 log.py:info:117 INFO] [cached since 3.171s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 26, 899279), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.459s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.448s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 175856), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.545s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.534s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 262411), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.613s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.603s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 331280), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.672s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.663s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 391315), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.73s ago] {'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 3.939s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 667075), 'feature_name_1': 'third_data_source#td_fs_Fscore', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.024s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.011s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 738873), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.085s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.084s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 811679), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.151s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.138s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 866614), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:27 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:27 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.211s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:27 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:27 log.py:info:117 INFO] [cached since 4.199s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 27, 927330), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:27 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:28 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:28 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.489s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:28 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.474s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 28, 202496), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:28 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:28 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:28 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.543s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:28 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.532s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 28, 260339), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:28 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:28 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:28 log.py:info:117 INFO] SELECT feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_content AS feature_detail_feature_content, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round, feature_detail.is_active AS feature_detail_is_active, feature_detail.create_at AS feature_detail_create_at, feature_detail.update_at AS feature_detail_update_at
FROM feature_detail
WHERE feature_detail.feature_name = %(feature_name_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.602s ago] {'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:28 log.py:info:117 INFO] UPDATE feature_detail SET is_active=%(is_active)s, update_at=%(update_at)s WHERE feature_detail.feature_name = %(feature_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 4.596s ago] {'is_active': 2, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 28, 324454), 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'is_active_1': 1}
[2021-04-26 15:43:28 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:28 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [generated in 0.00033s] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '1-100', 'feature_gdp': 20, 'data_type': 1, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.01072s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '0.1-1', 'feature_gdp': 15, 'data_type': 2, 'data_round': 6, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.02221s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': None, 'feature_gdp': 15, 'data_type': 3, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.03608s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': '-9999999', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.04817s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': 'None', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.05947s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '字符串', 'feature_value': None, 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.09302s ago] {'feature_name': 'third_data_source#pinTai_tb_score3', 'feature_content': '自动生成', 'feature_type': '整数', 'feature_value': '0', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.3259s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '1-100', 'feature_gdp': 20, 'data_type': 1, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.3375s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '0.1-1', 'feature_gdp': 15, 'data_type': 2, 'data_round': 6, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.3493s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': None, 'feature_gdp': 15, 'data_type': 3, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.3611s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': '-9999999', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:28 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:28 log.py:info:117 INFO] [cached since 0.3724s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': 'None', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.541s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '字符串', 'feature_value': None, 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.553s ago] {'feature_name': 'third_data_source#tc_universal_model_score', 'feature_content': '自动生成', 'feature_type': '整数', 'feature_value': '0', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.564s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '1-100', 'feature_gdp': 20, 'data_type': 1, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.58s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '0.1-1', 'feature_gdp': 15, 'data_type': 2, 'data_round': 6, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.592s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': None, 'feature_gdp': 15, 'data_type': 3, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.606s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': '-9999999', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:29 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:29 log.py:info:117 INFO] [cached since 1.617s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': 'None', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.631s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '字符串', 'feature_value': None, 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.668s ago] {'feature_name': 'third_data_source#xy_model3_score', 'feature_content': '自动生成', 'feature_type': '整数', 'feature_value': '0', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.768s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '1-100', 'feature_gdp': 20, 'data_type': 1, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.778s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '0.1-1', 'feature_gdp': 15, 'data_type': 2, 'data_round': 6, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.789s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': None, 'feature_gdp': 15, 'data_type': 3, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.8s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': '-9999999', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.81s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': 'None', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.821s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '字符串', 'feature_value': None, 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.831s ago] {'feature_name': 'third_data_source#td_fs_Fscore', 'feature_content': '自动生成', 'feature_type': '整数', 'feature_value': '0', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.842s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '1-100', 'feature_gdp': 20, 'data_type': 1, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.854s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': '0.1-1', 'feature_gdp': 15, 'data_type': 2, 'data_round': 6, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.866s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '区间', 'feature_value': None, 'feature_gdp': 15, 'data_type': 3, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.877s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': '-9999999', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.888s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '异常', 'feature_value': 'None', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.906s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '字符串', 'feature_value': None, 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] INSERT INTO feature_detail (feature_name, feature_content, feature_type, feature_value, feature_gdp, data_type, data_round, is_active, create_at, update_at) VALUES (%(feature_name)s, %(feature_content)s, %(feature_type)s, %(feature_value)s, %(feature_gdp)s, %(data_type)s, %(data_round)s, %(is_active)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 1.921s ago] {'feature_name': 'third_data_source#brlhp_2_scorecust1', 'feature_content': '自动生成', 'feature_type': '整数', 'feature_value': '0', 'feature_gdp': 10, 'data_type': 0, 'data_round': 0, 'is_active': 1, 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685235), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 685264)}
[2021-04-26 15:43:30 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-26 15:43:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-26 15:43:30 log.py:info:117 INFO] [generated in 0.00027s] {}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-26 15:43:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:30 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT data_set.id AS data_set_id, data_set.model_name AS data_set_model_name, data_set.user_count AS data_set_user_count, data_set.feature_name AS data_set_feature_name, data_set.create_at AS data_set_create_at, data_set.update_at AS data_set_update_at
FROM data_set
WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [generated in 0.00093s] {'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#pinTai_tb_score3', 'param_1': 1}
[2021-04-26 15:43:30 log.py:info:117 INFO] UPDATE data_set SET user_count=%(user_count)s, update_at=%(update_at)s WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [generated in 0.00057s] {'user_count': 1, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 30, 525229), 'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#pinTai_tb_score3'}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT data_set.id AS data_set_id, data_set.model_name AS data_set_model_name, data_set.user_count AS data_set_user_count, data_set.feature_name AS data_set_feature_name, data_set.create_at AS data_set_create_at, data_set.update_at AS data_set_update_at
FROM data_set
WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.02714s ago] {'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#tc_universal_model_score', 'param_1': 1}
[2021-04-26 15:43:30 log.py:info:117 INFO] UPDATE data_set SET user_count=%(user_count)s, update_at=%(update_at)s WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.02416s ago] {'user_count': 1, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 30, 550355), 'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#tc_universal_model_score'}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT data_set.id AS data_set_id, data_set.model_name AS data_set_model_name, data_set.user_count AS data_set_user_count, data_set.feature_name AS data_set_feature_name, data_set.create_at AS data_set_create_at, data_set.update_at AS data_set_update_at
FROM data_set
WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.04953s ago] {'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#xy_model3_score', 'param_1': 1}
[2021-04-26 15:43:30 log.py:info:117 INFO] UPDATE data_set SET user_count=%(user_count)s, update_at=%(update_at)s WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.04939s ago] {'user_count': 1, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 30, 575419), 'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#xy_model3_score'}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT data_set.id AS data_set_id, data_set.model_name AS data_set_model_name, data_set.user_count AS data_set_user_count, data_set.feature_name AS data_set_feature_name, data_set.create_at AS data_set_create_at, data_set.update_at AS data_set_update_at
FROM data_set
WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.2907s ago] {'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#td_fs_Fscore', 'param_1': 1}
[2021-04-26 15:43:30 log.py:info:117 INFO] UPDATE data_set SET user_count=%(user_count)s, update_at=%(update_at)s WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.3149s ago] {'user_count': 1, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 30, 841020), 'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#td_fs_Fscore'}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT data_set.id AS data_set_id, data_set.model_name AS data_set_model_name, data_set.user_count AS data_set_user_count, data_set.feature_name AS data_set_feature_name, data_set.create_at AS data_set_create_at, data_set.update_at AS data_set_update_at
FROM data_set
WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.3419s ago] {'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#brlhp_2_scorecust1', 'param_1': 1}
[2021-04-26 15:43:30 log.py:info:117 INFO] UPDATE data_set SET user_count=%(user_count)s, update_at=%(update_at)s WHERE data_set.model_name = %(model_name_1)s AND data_set.feature_name = %(feature_name_1)s
[2021-04-26 15:43:30 log.py:info:117 INFO] [cached since 0.3408s ago] {'user_count': 1, 'update_at': datetime.datetime(2021, 4, 26, 15, 43, 30, 866569), 'model_name_1': 'fst_assemble_flx_v8_score', 'feature_name_1': 'third_data_source#brlhp_2_scorecust1'}
[2021-04-26 15:43:30 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-26 15:43:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-26 15:43:30 log.py:info:117 INFO] [generated in 0.00052s] {}
[2021-04-26 15:43:30 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-26 15:43:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:31 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:31 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00040s] {'model_name_1': 'fst_assemble_flx_v8_score', 'is_active_1': 1}
[2021-04-26 15:43:31 log.py:info:117 INFO] INSERT INTO data_set_datail (model_id, model_name, user_count, feature_name, report_type, data_path, create_at, update_at) VALUES (%(model_id)s, %(model_name)s, %(user_count)s, %(feature_name)s, %(report_type)s, %(data_path)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00038s] {'model_id': 38, 'model_name': 'fst_assemble_flx_v8_score', 'user_count': 1, 'feature_name': 'third_data_source#brlhp_2_scorecust1,third_data_source#pinTai_tb_score3,third_data_source#xy_model3_score,third_data_source#td_fs_Fscore,third_data_source#tc_universal_model_score', 'report_type': 1, 'data_path': 'suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/data/data_fst_assemble_flx_v8_score.json', 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 691718), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 691749)}
[2021-04-26 15:43:31 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:31 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:31 log.py:info:117 INFO] INSERT INTO data_set_datail (model_id, model_name, user_count, feature_name, report_type, data_path, create_at, update_at) VALUES (%(model_id)s, %(model_name)s, %(user_count)s, %(feature_name)s, %(report_type)s, %(data_path)s, %(create_at)s, %(update_at)s)
[2021-04-26 15:43:31 log.py:info:117 INFO] [cached since 0.1187s ago] {'model_id': 38, 'model_name': 'fst_assemble_flx_v8_score', 'user_count': 1, 'feature_name': 'third_data_source#brlhp_2_scorecust1,third_data_source#pinTai_tb_score3,third_data_source#xy_model3_score,third_data_source#td_fs_Fscore,third_data_source#tc_universal_model_score', 'report_type': 2, 'data_path': 'suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/detail/detail_fst_assemble_flx_v8_score.json', 'create_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 691718), 'update_at': datetime.datetime(2021, 4, 26, 14, 47, 30, 691749)}
[2021-04-26 15:43:31 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:31 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:31 log.py:info:117 INFO] SELECT data_set_datail.id AS data_set_datail_id, data_set_datail.model_id AS data_set_datail_model_id, data_set_datail.model_name AS data_set_datail_model_name, data_set_datail.user_count AS data_set_datail_user_count, data_set_datail.feature_name AS data_set_datail_feature_name, data_set_datail.report_type AS data_set_datail_report_type, data_set_datail.data_path AS data_set_datail_data_path, data_set_datail.create_at AS data_set_datail_create_at, data_set_datail.update_at AS data_set_datail_update_at
FROM data_set_datail
WHERE data_set_datail.model_name = %(model_name_1)s AND data_set_datail.data_path = %(data_path_1)s AND data_set_datail.report_type = %(report_type_1)s
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00028s] {'model_name_1': 'fst_assemble_flx_v8_score', 'data_path_1': 'suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/detail/detail_fst_assemble_flx_v8_score.json', 'report_type_1': 2}
[2021-04-26 15:43:31 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-26 15:43:31 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:31 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00044s] {}
[2021-04-26 15:43:31 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-26 15:43:31 log.py:info:117 INFO] [raw sql] {}
[2021-04-26 15:43:31 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:31 log.py:info:117 INFO] SELECT data_set_datail.id AS data_set_datail_id, data_set_datail.model_name AS data_set_datail_model_name
FROM data_set_datail
WHERE data_set_datail.data_path = %(data_path_1)s
LIMIT %(param_1)s
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00035s] {'data_path_1': 'suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/detail/detail_fst_assemble_flx_v8_score.json', 'param_1': 1}
[2021-04-26 15:43:31 log.py:info:117 INFO] INSERT INTO user_test (data_set_datail_id, model_name, batch_uuid, data_detail) VALUES (%(data_set_datail_id)s, %(model_name)s, %(batch_uuid)s, %(data_detail)s)
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00034s] {'data_set_datail_id': 152, 'model_name': 'fst_assemble_flx_v8_score', 'batch_uuid': '6ee8f8fe0b6bc7543c287c1d9b3e7d5b', 'data_detail': "{'code': 200, 'data': {'features': {'third_data_source#brlhp_2_scorecust1': {'state': 200, 'value': 43}, 'third_data_source#pinTai_tb_score3': {'stat ... (78 characters truncated) ... 200, 'value': 60}, 'third_data_source#td_fs_Fscore': {'state': 200, 'value': 11}, 'third_data_source#xy_model3_score': {'state': 200, 'value': 1}}}}"}
[2021-04-26 15:43:31 log.py:info:117 INFO] COMMIT
[2021-04-26 15:43:31 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-26 15:43:31 log.py:info:117 INFO] SELECT user_test.batch_uuid AS user_test_batch_uuid, user_test.data_detail AS user_test_data_detail
FROM user_test
WHERE user_test.model_name = %(model_name_1)s AND user_test.data_set_datail_id = %(data_set_datail_id_1)s
[2021-04-26 15:43:31 log.py:info:117 INFO] [generated in 0.00030s] {'model_name_1': 'fst_assemble_flx_v8_score', 'data_set_datail_id_1': 152}
[2021-04-26 15:43:31 web.py:log_request:2243 INFO] 200 POST /api/automatic (::1) 9233.96ms
logs/2021-04-27.log 0 → 100644
View file @ 052263d5
[2021-04-27 10:22:28 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:22:28 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:22:28 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:22:28 log.py:info:117 INFO] [generated in 0.00049s] {}
[2021-04-27 10:22:28 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:22:28 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:22:29 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:22:29 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-27 10:22:29 log.py:info:117 INFO] [generated in 0.00037s] {'name_1': 'fst_assemble_lx_v8_score'}
[2021-04-27 10:22:29 log.py:info:117 INFO] INSERT INTO models_datail (name, content, create_name, el_expression, create_at, update_at) VALUES (%(name)s, %(content)s, %(create_name)s, %(el_expression)s, %(create_at)s, %(update_at)s)
[2021-04-27 10:22:29 log.py:info:117 INFO] [generated in 0.00047s] {'name': 'fst_assemble_lx_v8_score', 'content': '自动生成', 'create_name': '自动', 'el_expression': None, 'create_at': datetime.datetime(2021, 4, 27, 10, 21, 57, 988153), 'update_at': datetime.datetime(2021, 4, 27, 10, 21, 57, 988299)}
[2021-04-27 10:22:29 log.py:info:117 INFO] COMMIT
[2021-04-27 10:22:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:22:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:22:30 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:22:30 log.py:info:117 INFO] [generated in 0.00075s] {}
[2021-04-27 10:22:30 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:22:30 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:22:30 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:22:30 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-27 10:22:30 log.py:info:117 INFO] [generated in 0.00041s] {'model_name_1': 'fst_assemble_lx_v8_score', 'is_active_1': 1}
[2021-04-27 10:22:30 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (127.0.0.1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='127.0.0.1')
Traceback (most recent call last):
File "/Users/dm/.virtualenvs/model-data-test-0EaRlSf6/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 33, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 72, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-04-27 10:22:30 web.py:log_request:2243 ERROR] 500 POST /api/automatic (127.0.0.1) 2100.73ms
[2021-04-27 10:25:27 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:25:27 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:25:28 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:25:28 log.py:info:117 INFO] [generated in 0.00068s] {}
[2021-04-27 10:25:28 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:25:28 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:25:28 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:25:28 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-27 10:25:28 log.py:info:117 INFO] [generated in 0.00035s] {'name_1': 'fst_assemble_lx_v8_score'}
[2021-04-27 10:25:29 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:25:29 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:25:29 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:25:29 log.py:info:117 INFO] [generated in 0.00025s] {}
[2021-04-27 10:25:29 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:25:29 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:25:29 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:25:29 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-27 10:25:29 log.py:info:117 INFO] [generated in 0.00051s] {'model_name_1': 'fst_assemble_lx_v8_score', 'is_active_1': 1}
[2021-04-27 10:25:29 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (127.0.0.1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='127.0.0.1')
Traceback (most recent call last):
File "/Users/dm/.virtualenvs/model-data-test-0EaRlSf6/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 33, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 72, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-04-27 10:25:29 web.py:log_request:2243 ERROR] 500 POST /api/automatic (127.0.0.1) 4117.65ms
[2021-04-27 10:26:26 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:26:26 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:26:26 log.py:info:117 INFO] [generated in 0.00048s] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:26:26 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:26:26 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-27 10:26:26 log.py:info:117 INFO] [generated in 0.00031s] {'name_1': 'fst_assemble_lx_v8_score'}
[2021-04-27 10:26:26 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:26:26 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:26:26 log.py:info:117 INFO] [generated in 0.00046s] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:26:26 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:26:26 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:26:26 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-27 10:26:26 log.py:info:117 INFO] [generated in 0.00038s] {'model_name_1': 'fst_assemble_lx_v8_score', 'is_active_1': 1}
[2021-04-27 10:26:26 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Users/dm/.virtualenvs/model-data-test-0EaRlSf6/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 33, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 72, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-04-27 10:26:26 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 296.92ms
[2021-04-27 10:27:01 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:27:01 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:27:01 log.py:info:117 INFO] [generated in 0.00058s] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:27:01 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:27:01 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-27 10:27:01 log.py:info:117 INFO] [generated in 0.00044s] {'name_1': 'fst_assemble_lx_v8_score'}
[2021-04-27 10:27:01 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:27:01 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:27:01 log.py:info:117 INFO] [generated in 0.00046s] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:27:01 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:27:01 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:27:01 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-04-27 10:27:01 log.py:info:117 INFO] [generated in 0.00041s] {'model_name_1': 'fst_assemble_lx_v8_score', 'is_active_1': 1}
[2021-04-27 10:27:01 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Users/dm/.virtualenvs/model-data-test-0EaRlSf6/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 33, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 72, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-04-27 10:27:01 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 329.12ms
[2021-04-27 10:35:02 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-04-27 10:35:02 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:35:02 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-04-27 10:35:02 log.py:info:117 INFO] [generated in 0.00364s] {}
[2021-04-27 10:35:02 log.py:info:117 INFO] SELECT DATABASE()
[2021-04-27 10:35:02 log.py:info:117 INFO] [raw sql] {}
[2021-04-27 10:35:02 log.py:info:117 INFO] BEGIN (implicit)
[2021-04-27 10:35:02 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-04-27 10:35:02 log.py:info:117 INFO] [generated in 0.00435s] {'name_1': 'fst_assemble_lx_v8_score'}
logs/2021-05-08.log 0 → 100644
View file @ 052263d5
[2021-05-08 16:22:35 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-05-08 16:22:35 log.py:info:117 INFO] [raw sql] {}
[2021-05-08 16:22:35 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-05-08 16:22:35 log.py:info:117 INFO] [generated in 0.00053s] {}
[2021-05-08 16:22:35 log.py:info:117 INFO] SELECT DATABASE()
[2021-05-08 16:22:35 log.py:info:117 INFO] [raw sql] {}
[2021-05-08 16:22:36 log.py:info:117 INFO] BEGIN (implicit)
[2021-05-08 16:22:36 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-05-08 16:22:36 log.py:info:117 INFO] [generated in 0.00038s] {'name_1': 'model_exec_data_source#fst_assemble_flx_v8_score'}
[2021-05-08 16:22:36 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-05-08 16:22:36 log.py:info:117 INFO] [raw sql] {}
[2021-05-08 16:22:36 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-05-08 16:22:36 log.py:info:117 INFO] [generated in 0.00059s] {}
[2021-05-08 16:22:36 log.py:info:117 INFO] SELECT DATABASE()
[2021-05-08 16:22:36 log.py:info:117 INFO] [raw sql] {}
[2021-05-08 16:22:36 log.py:info:117 INFO] BEGIN (implicit)
[2021-05-08 16:22:36 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-05-08 16:22:36 log.py:info:117 INFO] [generated in 0.00041s] {'model_name_1': 'model_exec_data_source#fst_assemble_flx_v8_score', 'is_active_1': 1}
[2021-05-08 16:22:36 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Users/dm/.virtualenvs/model-data-test-0EaRlSf6/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 33, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 72, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-05-08 16:22:36 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 1682.81ms
logs/2021-05-17.log 0 → 100644
View file @ 052263d5
This source diff could not be displayed because it is too large. You can view the blob instead.
logs/2021-12-30.log 0 → 100644
View file @ 052263d5
[2021-12-30 16:22:01 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connection.py", line 175, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/util/connection.py", line 96, in create_connection
raise err
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/util/connection.py", line 86, in create_connection
sock.connect(sa)
ConnectionRefusedError: [Errno 61] Connection refused
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connectionpool.py", line 706, in urlopen
chunked=chunked,
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connectionpool.py", line 394, in _make_request
conn.request(method, url, **httplib_request_kw)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connection.py", line 239, in request
super(HTTPConnection, self).request(method, url, body=body, headers=headers)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/http/client.py", line 1229, in request
self._send_request(method, url, body, headers, encode_chunked)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/http/client.py", line 1275, in _send_request
self.endheaders(body, encode_chunked=encode_chunked)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/http/client.py", line 1224, in endheaders
self._send_output(message_body, encode_chunked=encode_chunked)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/http/client.py", line 1016, in _send_output
self.send(msg)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/http/client.py", line 956, in send
self.connect()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connection.py", line 205, in connect
conn = self._new_conn()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connection.py", line 187, in _new_conn
self, "Failed to establish a new connection: %s" % e
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7fb82d2505f8>: Failed to establish a new connection: [Errno 61] Connection refused
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/connectionpool.py", line 756, in urlopen
method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/urllib3/util/retry.py", line 574, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='172.21.10.25', port=9012): Max retries exceeded with url: /manage/features (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fb82d2505f8>: Failed to establish a new connection: [Errno 61] Connection refused'))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 28, in post
r = requests.post(url,data={'codes':self.model_name})
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/api.py", line 117, in post
return request('post', url, data=data, json=json, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/sessions.py", line 542, in request
resp = self.send(prep, **send_kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/sessions.py", line 655, in send
r = adapter.send(request, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='172.21.10.25', port=9012): Max retries exceeded with url: /manage/features (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fb82d2505f8>: Failed to establish a new connection: [Errno 61] Connection refused'))
[2021-12-30 16:22:01 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 2030.64ms
[2021-12-30 16:24:16 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 13, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 72, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 16:24:16 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 95.09ms
[2021-12-30 16:38:40 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_test/settings.py modified; restarting server
[2021-12-30 16:38:47 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_test/settings.py modified; restarting server
[2021-12-30 16:38:55 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 13, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 72, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 16:38:55 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 121.79ms
[2021-12-30 16:41:16 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 13, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 73, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 16:41:16 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 264.12ms
[2021-12-30 17:17:30 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py modified; restarting server
[2021-12-30 17:17:46 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 13, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 73, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 17:17:46 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 178.73ms
[2021-12-30 17:18:03 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py modified; restarting server
[2021-12-30 17:18:09 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 13, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 73, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 17:18:09 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 456.76ms
[2021-12-30 17:19:24 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 14, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 73, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 17:19:24 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 1090.89ms
[2021-12-30 17:24:01 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py modified; restarting server
[2021-12-30 17:24:15 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 56, in get_auto
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/logic.py", line 14, in add_models_logic
if not session.find_single(models_name):
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/modelsData_model.py", line 10, in find_single
return self.get_json(self.session.query(TabModelsData).filter_by(name = name))
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/model/base_model.py", line 73, in get_json
raise TypeError('Type error of parameter')
TypeError: Type error of parameter
[2021-12-30 17:24:15 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 551.19ms
[2021-12-30 17:26:15 autoreload.py:_check_file:201 INFO] /Users/dm/Desktop/python_script/model-data-test/model_data_test/settings.py modified; restarting server
[2021-12-30 17:27:48 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:27:48 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:27:48 log.py:info:117 INFO] [generated in 0.00032s] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:27:48 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:27:48 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-12-30 17:27:48 log.py:info:117 INFO] [generated in 0.00034s] {'name_1': 'ss_model_v10'}
[2021-12-30 17:27:48 log.py:info:117 INFO] INSERT INTO models_datail (name, content, create_name, el_expression, create_at, update_at) VALUES (%(name)s, %(content)s, %(create_name)s, %(el_expression)s, %(create_at)s, %(update_at)s)
[2021-12-30 17:27:48 log.py:info:117 INFO] [generated in 0.00036s] {'name': 'ss_model_v10', 'content': '自动生成', 'create_name': '自动', 'el_expression': None, 'create_at': datetime.datetime(2021, 12, 30, 17, 27, 45, 312047), 'update_at': datetime.datetime(2021, 12, 30, 17, 27, 45, 312212)}
[2021-12-30 17:27:48 log.py:info:117 INFO] COMMIT
[2021-12-30 17:27:48 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:27:48 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:27:48 log.py:info:117 INFO] [generated in 0.00064s] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:27:48 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:27:48 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:27:48 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-12-30 17:27:48 log.py:info:117 INFO] [generated in 0.00046s] {'model_name_1': 'ss_model_v10', 'is_active_1': 1}
[2021-12-30 17:27:48 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 73, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-12-30 17:27:48 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 584.06ms
[2021-12-30 17:29:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:29:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:29:55 log.py:info:117 INFO] [generated in 0.00049s] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:29:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:29:55 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-12-30 17:29:55 log.py:info:117 INFO] [generated in 0.00040s] {'name_1': 'ss_model_v10'}
[2021-12-30 17:29:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:29:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:29:55 log.py:info:117 INFO] [generated in 0.00037s] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:29:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:29:55 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:29:55 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-12-30 17:29:55 log.py:info:117 INFO] [generated in 0.00032s] {'model_name_1': 'ss_model_v10', 'is_active_1': 1}
[2021-12-30 17:29:55 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 34, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 73, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-12-30 17:29:55 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 399.70ms
[2021-12-30 17:34:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:34:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:34:55 log.py:info:117 INFO] [generated in 0.00038s] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:34:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:34:55 log.py:info:117 INFO] SELECT models_datail.id AS models_datail_id, models_datail.name AS models_datail_name, models_datail.content AS models_datail_content, models_datail.create_name AS models_datail_create_name, models_datail.el_expression AS models_datail_el_expression, models_datail.create_at AS models_datail_create_at, models_datail.update_at AS models_datail_update_at
FROM models_datail
WHERE models_datail.name = %(name_1)s
[2021-12-30 17:34:55 log.py:info:117 INFO] [generated in 0.00080s] {'name_1': 'ss_model_v10'}
[2021-12-30 17:34:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'sql_mode'
[2021-12-30 17:34:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] SHOW VARIABLES LIKE 'lower_case_table_names'
[2021-12-30 17:34:55 log.py:info:117 INFO] [generated in 0.00050s] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] SELECT DATABASE()
[2021-12-30 17:34:55 log.py:info:117 INFO] [raw sql] {}
[2021-12-30 17:34:55 log.py:info:117 INFO] BEGIN (implicit)
[2021-12-30 17:34:55 log.py:info:117 INFO] SELECT data_set.model_name AS data_set_model_name, models_datail.id AS model_id, data_set.user_count AS data_set_user_count, feature_detail.id AS feature_detail_id, feature_detail.feature_name AS feature_detail_feature_name, feature_detail.feature_type AS feature_detail_feature_type, feature_detail.feature_value AS feature_detail_feature_value, feature_detail.feature_gdp AS feature_detail_feature_gdp, feature_detail.data_type AS feature_detail_data_type, feature_detail.data_round AS feature_detail_data_round
FROM data_set INNER JOIN feature_detail ON data_set.feature_name = feature_detail.feature_name INNER JOIN models_datail ON models_datail.name = data_set.model_name
WHERE data_set.model_name = %(model_name_1)s AND feature_detail.is_active = %(is_active_1)s
[2021-12-30 17:34:55 log.py:info:117 INFO] [generated in 0.00048s] {'model_name_1': 'ss_model_v10', 'is_active_1': 1}
[2021-12-30 17:34:55 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 35, in post
result = self.get_auto()
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 74, in get_auto
if result_add_userTest['code'] == 200:
TypeError: 'NoneType' object is not subscriptable
[2021-12-30 17:34:55 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 446.25ms
[2021-12-31 10:25:29 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 32, in post
self.feature_name = response['data'][self.model_name]['new']+response['data'][self.model_name]['old']
KeyError: 'ss_assemble_v10_score,reloan_assemble_v10_score'
[2021-12-31 10:25:29 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 242.05ms
[2021-12-31 10:25:44 web.py:log_exception:1793 ERROR] Uncaught exception POST /api/automatic (::1)
HTTPServerRequest(protocol='http', host='localhost:23020', method='POST', uri='/api/automatic', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tornado/web.py", line 1702, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "/Users/dm/Desktop/python_script/model-data-test/model_data_api/handler/Automatic_Handler.py", line 32, in post
self.feature_name = response['data'][self.model_name]['new']+response['data'][self.model_name]['old']
KeyError: 'ss_assemble_v10_score,reloan_assemble_v10_score'
[2021-12-31 10:25:44 web.py:log_request:2243 ERROR] 500 POST /api/automatic (::1) 2044.10ms
[2022-01-04 16:05:11 base.py:_finalize_fairy:766 ERROR] Exception during reset or similar
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 756, in _write_bytes
self._sock.sendall(data)
BrokenPipeError: [Errno 32] Broken pipe
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/pool/base.py", line 739, in _finalize_fairy
fairy._reset(pool)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/pool/base.py", line 988, in _reset
pool._dialect.do_rollback(self)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/engine/default.py", line 669, in do_rollback
dbapi_connection.rollback()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 479, in rollback
self._execute_command(COMMAND.COM_QUERY, "ROLLBACK")
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 814, in _execute_command
self._write_bytes(packet)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 760, in _write_bytes
CR.CR_SERVER_GONE_ERROR, "MySQL server has gone away (%r)" % (e,)
pymysql.err.OperationalError: (2006, "MySQL server has gone away (BrokenPipeError(32, 'Broken pipe'))")
[2022-01-04 16:05:11 base.py:_finalize_fairy:766 ERROR] Exception during reset or similar
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 756, in _write_bytes
self._sock.sendall(data)
BrokenPipeError: [Errno 32] Broken pipe
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/pool/base.py", line 739, in _finalize_fairy
fairy._reset(pool)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/pool/base.py", line 988, in _reset
pool._dialect.do_rollback(self)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sqlalchemy/engine/default.py", line 669, in do_rollback
dbapi_connection.rollback()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 479, in rollback
self._execute_command(COMMAND.COM_QUERY, "ROLLBACK")
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 814, in _execute_command
self._write_bytes(packet)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pymysql/connections.py", line 760, in _write_bytes
CR.CR_SERVER_GONE_ERROR, "MySQL server has gone away (%r)" % (e,)
pymysql.err.OperationalError: (2006, "MySQL server has gone away (BrokenPipeError(32, 'Broken pipe'))")
logs/2022-02-08.log 0 → 100644
View file @ 052263d5
This source diff could not be displayed because it is too large. You can view the blob instead.
model_data_api/handler/Automatic_Handler.py
View file @ 052263d5
......@@ -29,7 +29,7 @@ class AutomaticHandler(BaseHandler):
if r.status_code == 200:
response = r.json()
self.feature_name = response['data'][self.model_name]['new']+response['data'][self.model_name]['old']
print('获取模型新旧数据：',self.feature_name)
result = self.get_auto()
self.write(JsonUtil.build_json_data(code=result['code'],
message=result['message'],
......@@ -61,20 +61,23 @@ class AutomaticHandler(BaseHandler):
userTestData = UserTestDataManager()
result_model = add_models_logic(modelsData,self.model_name,'自动生成','自动')
print("模型创建结果:",result_model)
for f in self.feature_name:
self.auto_feature.append({'feature_name':f,'feature_content':'自动生成','assert_name':'模型测试'})
result_feature = add_features_logic(featureData,self.auto_feature)
print('添加特征结果：',result_feature)
for f in self.auto_feature:
self.auto_dataset['data_detail'].append(f)
result_dataset = set_modelsAndfeature_logic(dataSet,self.auto_dataset)
print("模型和特征挂钩结果：",result_dataset)
result_datasetdetail = create_dataSet_logic(dataSetDetail,self.model_name,common)
print("创建测试数据目录备份测试数据文件：",result_datasetdetail)
result_add_userTest = None
if result_datasetdetail['code'] == 200:
result_add_userTest = add_userTest_logic(userTestData,result_datasetdetail['result']['detail_path'],common)
result_add_userTest = add_userTest_logic(userTestData,result_datasetdetail['result']['detail_path'],common,isTrue=common.get('ISTRUE'))
result_userTest = None
if result_add_userTest['code'] == 200:
......
model_data_api/handler/logic.py
View file @ 052263d5
......@@ -129,7 +129,7 @@ def create_dataSet_logic(session,model_name,common):
_result = get_array(_id,_gdp_num,_type,_value,_data_type,_data_round)
result[k] = _result
print('1----')
_path ,_tree,_treeDetail = create_suiteFile(common,model_name,datetime.datetime.now())
_data = os.path.join(_treeDetail['path'],_treeDetail['name'][0],'data_%s.json'%(model_name))
_detail = os.path.join(_treeDetail['path'],_treeDetail['name'][1],'detail_%s.json'%(model_name))
......@@ -165,7 +165,7 @@ def create_dataSet_logic(session,model_name,common):
'code':JsonUtil.Constants.Code_Success,'message':JsonUtil.Constants.Msg_Success}
def add_userTest_logic(session,file_path,common):
def add_userTest_logic(session,file_path,common,isTrue=True):
result = {}
if file_path:
with open(get_path(common,'suite',file_path), 'r',encoding='utf8') as f:
......@@ -175,7 +175,12 @@ def add_userTest_logic(session,file_path,common):
_df_result = pd.DataFrame(result)
_df_result['result'] = _df_result.apply(lambda x : get_change(x),axis=1)
_df_result['batch_uuid'] = None
_df_result['batch_uuid'] = _df_result['batch_uuid'] .apply(lambda x : hashlib.md5(str(datetime.datetime.now()).encode(encoding='UTF-8')).hexdigest())
if not isTrue:
_df_result['batch_uuid'] = _df_result['batch_uuid'] .apply(lambda x : hashlib.md5(str(datetime.datetime.now()).encode(encoding='UTF-8')).hexdigest())
else:
uuid_path=get_path(common,'DATA','uuid.csv')
_df_result['batch_uuid']=pd.read_csv(uuid_path,encoding='utf-8')['uuid'][:len(result)]
batch_uuid = _df_result['batch_uuid'].tolist()
data_detail = _df_result['result'].tolist()
......
model_data_api/model/dataSetDetail_model.py
View file @ 052263d5
......@@ -14,13 +14,19 @@ class DataSetDetailManager(BaseManager):
TabDataSet.feature_name==TabFeatureData.feature_name
).join(TabModelsData,TabModelsData.name ==TabDataSet.model_name
).filter(TabDataSet.model_name == model_name,TabFeatureData.is_active==1)
# values = self.session.execute(query).fetchall()
#query = self.session.execute(query).fetchall()
result = {}
#print('query==>',query)
temp=['model_name', 'model_id', 'user_count']
temp_3=['id', 'feature_name', 'feature_type', 'feature_value', 'feature_gdp', 'data_type', 'data_round']
for i ,res in enumerate(query):
#print('datasetDetail==',i,'---',res,type(res))
if not result:
result=dict(result,**dict(zip(res.keys()[0:3],list(res[0:3]))))
# print('keys==',res,res.keys())
# print('keys==',res,list(res[0:3]))
result=dict(result,**dict(zip(temp,list(res[0:3]))))
result['data'] = []
result['data'].append(dict(zip(res.keys()[3:],list(res[3:]))))
result['data'].append(dict(zip(temp_3,list(res[3:]))))
# result = {}
# data = {}
......
model_data_api/model/featureData_model.py
View file @ 052263d5
......@@ -16,8 +16,11 @@ class FeatureDataManager(BaseManager):
TabAssertData.assert_type,TabAssertData.assert_value,
TabAssertData.assert_gdp,TabAssertData.data_type,TabAssertData.data_round
).filter_by(assert_name=assert_name)
for i ,res in enumerate(query):
print('feature res===',res)
result.append(dict(zip(res.keys(),list(res))))
print('feature result===',result)
return result
......
model_data_test/settings.py
View file @ 052263d5
......@@ -32,7 +32,7 @@ DB_CONNECT_STRING = None
# if DEBUG:
if AMBIENT == 'dev' or AMBIENT =='test':
DB_CONNECT_STRING = { # 支持多个数据库
'model_db':'mysql+pymysql://qa:qatest@172.17.5.13:30267/model_data_test?charset=utf8',
'model_db':'mysql+pymysql://qa:qatest@172.17.5.2:30081/model_data_test?charset=utf8',
#'model_db':'mysql+pymysql://root:root@127.0.0.1:3306/model_data_test?charset=utf8',
}
elif AMBIENT == 'online':
......@@ -50,5 +50,7 @@ common = dict(
static_url_prefix=os.path.join(BASE_DIR, "/static/"),
autoreload = True,
DEBUG = DEBUG,
suite = os.path.join(BASE_DIR,"")
suite = os.path.join(BASE_DIR,""),
DATA =os.path.join(BASE_DIR,"data"),
ISTRUE=1
)
suite/fs_assemble_v11_score/2022-02-08 15-41-41-445163/data/data_fs_assemble_v11_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fs_assemble_v11_score",
"model_id": 53,
"user_count": 1,
"data": [
{
"id": 4047,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4048,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4049,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4050,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4051,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4052,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4053,
"feature_name": "offline_base_feature#stored_addr_num",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4054,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4055,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4056,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4057,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4058,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4059,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4060,
"feature_name": "third_data_source#union_pay_advisors_UPPD029",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4061,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4062,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4063,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4064,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4065,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4066,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4067,
"feature_name": "third_data_source#union_pay_advisors_UPPD005",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4068,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4069,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4070,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4071,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4072,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4073,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4074,
"feature_name": "third_data_source#union_pay_advisors_UPPA009",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4075,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4076,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4077,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4078,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4079,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4080,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4081,
"feature_name": "third_data_source#union_pay_advisors_UPPD001",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4082,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4083,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4084,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4085,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4086,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4087,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4088,
"feature_name": "third_data_source#union_pay_advisors_UPPE075",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4089,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4090,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4091,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4092,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4093,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4094,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4095,
"feature_name": "offline_behavior_feature#purchased_orderno",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4096,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4097,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4098,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4099,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4100,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4101,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4102,
"feature_name": "third_data_source#union_pay_advisors_UPPC075",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4103,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4104,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4105,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4106,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4107,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4108,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4109,
"feature_name": "third_data_source#union_pay_advisors_UPPC073",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4110,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4111,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4112,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4113,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4114,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4115,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4116,
"feature_name": "third_data_source#union_pay_advisors_UPPE015",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4117,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4118,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4119,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4120,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4121,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4122,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4123,
"feature_name": "offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4124,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4125,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4126,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4127,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4128,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4129,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4130,
"feature_name": "offline_behavior_feature#user_clk_rc_sku_max_price_7d",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4131,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4132,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4133,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4134,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4135,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4136,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4137,
"feature_name": "third_data_source#union_pay_advisors_UPPC146",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4138,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4139,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4140,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4141,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4142,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4143,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4144,
"feature_name": "third_data_source#union_pay_advisors_UPPE047",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4145,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4146,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4147,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4148,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4149,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4150,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4151,
"feature_name": "third_data_source#union_pay_advisors_UPPC244",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4152,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4153,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4154,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4155,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4156,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4157,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4158,
"feature_name": "third_data_source#union_pay_advisors_UPPC242",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4159,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4160,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4161,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4162,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4163,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4164,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4165,
"feature_name": "third_data_source#union_pay_advisors_UPPC191",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4166,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4167,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4168,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4169,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4170,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4171,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4172,
"feature_name": "third_data_source#union_pay_advisors_UPPD010",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4173,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4174,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4175,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4176,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4177,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4178,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4179,
"feature_name": "third_data_source#union_pay_advisors_UPPE050",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4180,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4181,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4182,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4183,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4184,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4185,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4186,
"feature_name": "third_data_source#union_pay_advisors_UPPD025",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4187,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4188,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4189,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4190,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4191,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4192,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4193,
"feature_name": "third_data_source#union_pay_advisors_UPPE080",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4194,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4195,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4196,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4197,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4198,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4199,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4200,
"feature_name": "third_data_source#union_pay_advisors_UPPC174",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4201,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4202,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4203,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4204,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4205,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4206,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4207,
"feature_name": "third_data_source#union_pay_advisors_UPPE073",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4208,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4209,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4210,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4211,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4212,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4213,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4214,
"feature_name": "third_data_source#union_pay_advisors_UPPE016",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4215,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4216,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4217,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4218,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4219,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4220,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4221,
"feature_name": "offline_behavior_feature#user_clk_all_sku_max_price_7d",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4222,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4223,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4224,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4225,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4226,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4227,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4228,
"feature_name": "third_data_source#union_pay_advisors_UPPC071",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4229,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4230,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4231,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4232,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4233,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4234,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4235,
"feature_name": "third_data_source#union_pay_advisors_UPPC189",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4236,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4237,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4238,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4239,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4240,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4241,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4242,
"feature_name": "third_data_source#union_pay_advisors_UPPE079",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4243,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4244,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4245,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4246,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4247,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4248,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4249,
"feature_name": "third_data_source#union_pay_advisors_UPPE071",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4250,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4251,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4252,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4253,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4254,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4255,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4256,
"feature_name": "third_data_source#union_pay_advisors_UPPC094",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4257,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4258,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4259,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4260,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4261,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4262,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4263,
"feature_name": "offline_base_feature#purchased_addr_ambi_num",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4264,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4265,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4266,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4267,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4268,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4269,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4270,
"feature_name": "third_data_source#union_pay_advisors_UPPE031",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4271,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4272,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4273,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4274,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4275,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4276,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4277,
"feature_name": "third_data_source#union_pay_advisors_UPPE070",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
},
{
"id": 4278,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 4279,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 4280,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "区间",
"feature_value": "NULL",
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 4281,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4282,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4283,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "字符串",
"feature_value": "NULL",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 4284,
"feature_name": "third_data_source#union_pay_advisors_UPPE125",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 1,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fs_assemble_v11_score/2022-02-08 15-41-41-445163/detail/detail_fs_assemble_v11_score.json 0 → 100644
View file @ 052263d5
{
"offline_base_feature#purchased_addr_ambi_num": [
29
],
"offline_base_feature#stored_addr_num": [
33
],
"offline_behavior_feature#purchased_orderno": [
33
],
"offline_behavior_feature#user_clk_all_sku_max_price_7d": [
57
],
"offline_behavior_feature#user_clk_rc_sku_max_price_7d": [
83
],
"offline_behavior_feature#user_clk_sc_sku_max_frequence_price_7d": [
63
],
"third_data_source#union_pay_advisors_UPPA009": [
60
],
"third_data_source#union_pay_advisors_UPPC071": [
44
],
"third_data_source#union_pay_advisors_UPPC073": [
32
],
"third_data_source#union_pay_advisors_UPPC075": [
67
],
"third_data_source#union_pay_advisors_UPPC094": [
52
],
"third_data_source#union_pay_advisors_UPPC146": [
18
],
"third_data_source#union_pay_advisors_UPPC174": [
48
],
"third_data_source#union_pay_advisors_UPPC189": [
13
],
"third_data_source#union_pay_advisors_UPPC191": [
73
],
"third_data_source#union_pay_advisors_UPPC242": [
44
],
"third_data_source#union_pay_advisors_UPPC244": [
64
],
"third_data_source#union_pay_advisors_UPPD001": [
2
],
"third_data_source#union_pay_advisors_UPPD005": [
97
],
"third_data_source#union_pay_advisors_UPPD010": [
17
],
"third_data_source#union_pay_advisors_UPPD025": [
36
],
"third_data_source#union_pay_advisors_UPPD029": [
31
],
"third_data_source#union_pay_advisors_UPPE015": [
93
],
"third_data_source#union_pay_advisors_UPPE016": [
40
],
"third_data_source#union_pay_advisors_UPPE031": [
37
],
"third_data_source#union_pay_advisors_UPPE047": [
4
],
"third_data_source#union_pay_advisors_UPPE050": [
13
],
"third_data_source#union_pay_advisors_UPPE070": [
100
],
"third_data_source#union_pay_advisors_UPPE071": [
91
],
"third_data_source#union_pay_advisors_UPPE073": [
72
],
"third_data_source#union_pay_advisors_UPPE075": [
26
],
"third_data_source#union_pay_advisors_UPPE079": [
45
],
"third_data_source#union_pay_advisors_UPPE080": [
47
],
"third_data_source#union_pay_advisors_UPPE125": [
40
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-29-02-139215/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17592,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17593,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17594,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17595,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17596,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17597,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17598,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17599,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17600,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17601,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17602,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17603,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17604,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17605,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17606,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17607,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17608,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17609,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17610,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17611,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17612,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17613,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17614,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17615,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17616,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17617,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17618,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17619,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17620,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17621,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17622,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17623,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17624,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17625,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17626,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-29-02-139215/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
62,
83742
],
"third_data_source#pinTai_tb_score3": [
48,
204850.628585
],
"third_data_source#tc_universal_model_score": [
602176,
34
],
"third_data_source#td_fs_Fscore": [
425775.25222,
93
],
"third_data_source#xy_model3_score": [
793734,
44
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-32-56-782199/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17627,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17628,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17629,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17630,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17631,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17632,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17633,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17634,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17635,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17636,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17637,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17638,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17639,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17640,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17641,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17642,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17643,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17644,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17645,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17646,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17647,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17648,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17649,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17650,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17651,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17652,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17653,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17654,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17655,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17656,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17657,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17658,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17659,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17660,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17661,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-32-56-782199/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
856268.400515,
71
],
"third_data_source#pinTai_tb_score3": [
87,
854107.242335
],
"third_data_source#tc_universal_model_score": [
26,
567144
],
"third_data_source#td_fs_Fscore": [
78,
735635
],
"third_data_source#xy_model3_score": [
58,
717935
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-33-18-429548/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17662,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17663,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17664,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17665,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17666,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17667,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17668,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17669,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17670,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17671,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17672,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17673,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17674,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17675,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17676,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17677,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17678,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17679,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17680,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17681,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17682,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17683,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17684,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17685,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17686,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17687,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17688,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17689,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17690,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17691,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17692,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17693,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17694,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17695,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17696,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-33-18-429548/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
21,
395495
],
"third_data_source#pinTai_tb_score3": [
78960,
84
],
"third_data_source#tc_universal_model_score": [
574636,
84
],
"third_data_source#td_fs_Fscore": [
11481.07491,
81
],
"third_data_source#xy_model3_score": [
270754,
32
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-46-51-637443/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17697,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17698,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17699,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17700,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17701,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17702,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17703,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17704,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17705,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17706,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17707,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17708,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17709,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17710,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17711,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17712,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17713,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17714,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17715,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17716,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17717,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17718,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17719,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17720,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17721,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17722,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17723,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17724,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17725,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17726,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17727,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17728,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17729,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17730,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17731,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-46-51-637443/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
263456,
81
],
"third_data_source#pinTai_tb_score3": [
32,
170106
],
"third_data_source#tc_universal_model_score": [
59,
799853
],
"third_data_source#td_fs_Fscore": [
927103,
26
],
"third_data_source#xy_model3_score": [
902152.483966,
70
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-47-04-838051/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17732,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17733,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17734,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17735,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17736,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17737,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17738,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17739,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17740,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17741,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17742,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17743,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17744,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17745,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17746,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17747,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17748,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17749,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17750,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17751,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17752,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17753,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17754,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17755,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17756,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17757,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17758,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17759,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17760,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17761,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17762,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17763,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17764,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17765,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17766,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-47-04-838051/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
4,
870221
],
"third_data_source#pinTai_tb_score3": [
42,
643269
],
"third_data_source#tc_universal_model_score": [
18,
849534
],
"third_data_source#td_fs_Fscore": [
123051.03603,
96
],
"third_data_source#xy_model3_score": [
52,
78275
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-48-02-995048/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 2,
"data": [
{
"id": 17767,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17768,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17769,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17770,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17771,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17772,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17773,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17774,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17775,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17776,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17777,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17778,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17779,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17780,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17781,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17782,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17783,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17784,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17785,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17786,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17787,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17788,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17789,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17790,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17791,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17792,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17793,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17794,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17795,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17796,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17797,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17798,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17799,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17800,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17801,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-48-02-995048/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
959930.846377,
55
],
"third_data_source#pinTai_tb_score3": [
112634,
53
],
"third_data_source#tc_universal_model_score": [
379250,
4
],
"third_data_source#td_fs_Fscore": [
160574,
33
],
"third_data_source#xy_model3_score": [
475586,
11
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-51-33-329466/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 10000,
"data": [
{
"id": 17802,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17803,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17804,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17805,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17806,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17807,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17808,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17809,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17810,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17811,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17812,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17813,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17814,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17815,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17816,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17817,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17818,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17819,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17820,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17821,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17822,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17823,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17824,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17825,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17826,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17827,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17828,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17829,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17830,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17831,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17832,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17833,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17834,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17835,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17836,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-25 16-51-33-329466/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
This source diff could not be displayed because it is too large. You can view the blob instead.
suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/data/data_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_flx_v8_score",
"model_id": 38,
"user_count": 1,
"data": [
{
"id": 17844,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17845,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17846,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17847,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17848,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17849,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17850,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17865,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17866,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17867,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17868,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17869,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17870,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17871,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17851,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17852,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17853,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17854,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17855,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17856,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17857,
"feature_name": "third_data_source#xy_model3_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17858,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17859,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17860,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17861,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17862,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17863,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17864,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17837,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17838,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17839,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17840,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17841,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17842,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17843,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_flx_v8_score/2021-04-26 15-43-31-095100/detail/detail_fst_assemble_flx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
43
],
"third_data_source#pinTai_tb_score3": [
42
],
"third_data_source#tc_universal_model_score": [
60
],
"third_data_source#td_fs_Fscore": [
11
],
"third_data_source#xy_model3_score": [
1
]
}
\ No newline at end of file
suite/fst_assemble_lx_v8_score/2021-05-17 14-25-56-737077/data/data_fst_assemble_lx_v8_score.json 0 → 100644
View file @ 052263d5
{
"model_name": "fst_assemble_lx_v8_score",
"model_id": 39,
"user_count": 2,
"data": [
{
"id": 17977,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17978,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17979,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17980,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17981,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17982,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17983,
"feature_name": "third_data_source#ht_anti_fraud_a",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17984,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17985,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17986,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17987,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17988,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17989,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17990,
"feature_name": "third_data_source#brlhp_2_scorecust1",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17991,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17992,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 17993,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 17994,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17995,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17996,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17997,
"feature_name": "third_data_source#td_fs_Fscore",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 17998,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 17999,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 18000,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 18001,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18002,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18003,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18004,
"feature_name": "third_data_source#pinTai_tb_score3",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18005,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "1-100",
"feature_gdp": 20,
"data_type": 1,
"data_round": 0
},
{
"id": 18006,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": "0.1-1",
"feature_gdp": 15,
"data_type": 2,
"data_round": 6
},
{
"id": 18007,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "区间",
"feature_value": null,
"feature_gdp": 15,
"data_type": 3,
"data_round": 0
},
{
"id": 18008,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "-9999999",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18009,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "异常",
"feature_value": "None",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18010,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "字符串",
"feature_value": null,
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
},
{
"id": 18011,
"feature_name": "third_data_source#tc_universal_model_score",
"feature_type": "整数",
"feature_value": "0",
"feature_gdp": 10,
"data_type": 0,
"data_round": 0
}
]
}
\ No newline at end of file
suite/fst_assemble_lx_v8_score/2021-05-17 14-25-56-737077/detail/detail_fst_assemble_lx_v8_score.json 0 → 100644
View file @ 052263d5
{
"third_data_source#brlhp_2_scorecust1": [
3,
305031
],
"third_data_source#ht_anti_fraud_a": [
329929.872997,
63
],
"third_data_source#pinTai_tb_score3": [
728678,
40
],
"third_data_source#tc_universal_model_score": [
73,
324495
],
"third_data_source#td_fs_Fscore": [
50,
773159.832055
]
}
\ No newline at end of file
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment